We present cloud-tracking results from Venus nightside images with velocity errors approaching 1 m/s (rms). The cloud-tracking scheme focuses on 1) reducing the errors associated with Venus disk registration and 2) modeling cloud feature trajectories over a succession of images. Venus disk registration errors are reduced to within 0.25 pixels with a combination of limb detection from radial-gradients and robust rejection of outliers. Cloud tracking trajectories are modeled as simple functions of latitude and longitude using Advection Corrected Correlation Image Velocimetry (Asay-Davis et al., 2009). The cloud-tracking methods are then applied to two unique datasets to investigate cloud processes and global atmospheric circulation on Venus. The first dataset consists of an 18-hour time series of images with one-hour intervals of Venus' nightside at 1.74, 2.26, 2.32 μm acquired by the JAXA Akatsuki mission on August 25, 2016: these images were deconvolved to remove scattered light and improve acuity (Vun, 2020). The second dataset consists of images acquired by the NASA Infrared Telescope Facility and the Nordic Optical Telescope during coordinated campaigns in June and July 2020. The IRTF and NOT observations let us track a large cloud discontinuity (similar to features described by Peralta et al. (2020)) over a 10-hour period.

1: Asay-Davis, X.S. et al. (2009), Jupiter's shrinking Great Red Spot and steady Oval BA: Velocity measurements with the 'Advection Corrected Correlation Image Velocimetry' automated cloud-tracking method. 10.1016/j.icarus.2009.05.001 ; 2: Vun, C.W. et al. (2020), Enormous Cloud Cover on Venus observed by Akatsuki's IR2 data recovered by Restoration-by-Deconvolution (RD) method (submitted to Earth, Planets, and Space). DOI: 10.21203/rs.3.rs-26756/v1 ; 3: Peralta, J. et al. (2020), A Long-Lived Sharp Disruption on the Lower Clouds of Venus. DOI: 10.1029/2020GL087221